The overall objective of this project is to develop and initially evaluate a novel multidimensional ion mobility- mass spectrometry based high throughput metabolomics platform and associated automated informatics pipeline for analyses of biomedically and clinically relevant samples that will provide measurements that will be: much more robust, provide greater coverage and sensitivity, be more than an order of magnitude higher throughput, and have higher quantitative utility compared to present platforms. The new platform will exploit new developments in ionization, ion funnel technology, multidimensional ion mobility separations, and mass spectrometry interfacing. Improvements to the speed of the bioinformatics pipeline will be achieved in part by creating accurate mass and time (AMT) tag databases that utilize information from the multidimensional ion mobility separations in conjunction with accurate mass information to effectively identify previously cataloged metabolites and enable broad quantitative comparisons for different samples. The initially unknown metabolites observed in these measurements can also be compared across sample sets, and in many cases other detected species also identified based on their accurate masses, MS/MS data, and structurally related ion mobility information, and thus driving a continued expansion of the metabolite AMT tag database. The new platform and informatics pipeline will be initially evaluated and demonstrated using significant sets of blood spot and serum samples, and rapidly disseminated to make the technology more broadly available. PUBLIC HEALTH RELEVANCE: Metabolomics aims to provide a comprehensive approach to measure the functional output of biological pathways within biological systems that indicate characteristics of a disease, growth conditions, or other perturbations. The planned research will develop, evaluate, and initially demonstrate a new instrumental platform and associated automated informatics pipeline for analyses of biomedically and clinically relevant metabolomics samples with significantly improved sensitivity, coverage, and measurement throughput.